Computational Fluid Dynamics (CFD) Simulations of Spray Drying: Linking Drying Parameters with Experimental Aerosolization Performance.
Pharm Res
; 37(6): 101, 2020 May 21.
Article
em En
| MEDLINE
| ID: mdl-32440940
ABSTRACT
PURPOSE:
The purpose of this study was to develop a new computational fluid dynamics (CFD)-based model of the complex transport and droplet drying kinetics within a laboratory-scale spray dryer, and relate CFD-predicted drying parameters to powder aerosolization metrics from a reference dry powder inhaler (DPI).METHODS:
A CFD model of the Buchi Nano Spray Dryer B-90 was developed that captured spray dryer conditions from a previous experimental study producing excipient enhanced growth powders with L-leucine as a dispersion enhancer. The CFD model accounted for two-way heat and mass transfer coupling between the phases and turbulent flow created by acoustic streaming from the mesh nebulizer. CFD-based drying parameters were averaged across all droplets in each spray dryer case and included droplet time-averaged drying rate (κavg), maximum instantaneous drying rate (κmax) and precipitation window.RESULTS:
CFD results highlighted a chaotic drying environment in which time-averaged droplet drying rates (κavg) for each spray dryer case had high variability with coefficients of variation in the range of 60-70%. Maximum instantaneous droplet drying rates (κmax) were discovered that were two orders of magnitude above time-averaged drying rates. Comparing CFD-predicted drying parameters with experimentally determined mass median aerodynamic diameters (MMAD) and emitted doses (ED) from a reference DPI produced strong linear correlations with coefficients of determination as high as R2 = 0.98.CONCLUSIONS:
For the spray dryer system and conditions considered, reducing the CFD-predicted maximum drying rate experienced by droplets improved the aerosolization performance (both MMAD and ED) when the powders were aerosolized with a reference DPI.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Composição de Medicamentos
/
Excipientes
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Secagem por Atomização
/
Modelos Químicos
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article